Risk mitigation of AI
Lesson details
Learning outcome
I can describe the main risks of artificial intelligence and explain how risks can be reduced.
Key learning points
- AI systems can pose risks such as bias, job displacement, misuse and lack of transparency.
- AI risk mitigation involves strategies like ethical design, regulation, testing and human oversight.
- Governments, companies and individuals all play a role in reducing the potential harms of AI technologies.
Keywords
Transparency - being open and clear about how a system works
Mitigation - reducing the impact of a problem or risk
Regulation - creating and enforcing rules to guide how something is used
Human oversight - keeping people responsible for checking and controlling how AI systems are used
Common misconception
Once AI is built, it can’t be changed and the risks are already set.
AI systems can and should be continuously monitored, tested and improved to reduce risks. Risk mitigation is an ongoing process, not a one-time fix.
Teacher tip
Use real-life examples to show shared responsibility. For instance, ask learners what roles governments, companies and users should play if a social media platform spreads harmful misinformation with AI.
Licence
Lesson video
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Prior knowledge starter quiz
6 Questions
Q1.Which of the following best describes a deepfake?
Q2.Why might someone create a deepfake for negative purposes?
Q3.What is one positive use of deepfake technology?
Q4.Arrange these actions in the correct order for identifying a deepfake:
Q5.Which keyword means "false or inaccurate information"?
Q6.Match each keyword to its correct definition:
Assessment exit quiz
6 Questions
Q1.Which of the following is a risk associated with artificial intelligence?
Q2.Arrange the steps for ongoing risk mitigation in AI systems in the correct order:
Q3.What does "mitigation" mean in the context of AI risks?
Q4.Which group is responsible for reducing the risks of AI?
Q5.What is the key principle that ensures people can understand how an AI system makes its decisions?
Q6.Why is human oversight important in AI?
To help you plan your 10 computing lesson on: Risk mitigation of AI, download all teaching resources for free and adapt to suit your pupils' needs...
To help you plan your 10 computing lesson on: Risk mitigation of AI, download all teaching resources for free and adapt to suit your pupils' needs.
The starter quiz will activate and check your pupils' prior knowledge, with versions available both with and without answers in PDF format.
We use learning cycles to break down learning into key concepts or ideas linked to the learning outcome. Each learning cycle features explanations with checks for understanding and practice tasks with feedback. All of this is found in our slide decks, ready for you to download and edit. The practice tasks are also available as printable worksheets and some lessons have additional materials with extra material you might need for teaching the lesson.
The assessment exit quiz will test your pupils' understanding of the key learning points.
Our video is a tool for planning, showing how other teachers might teach the lesson, offering helpful tips, modelled explanations and inspiration for your own delivery in the classroom. Plus, you can set it as homework or revision for pupils and keep their learning on track by sharing an online pupil version of this lesson.
Explore more key stage 4 computing lessons from the Using data science and AI tools effectively and safely unit, dive into the full secondary computing curriculum, or learn more about lesson planning.